This paper proposes a conceptualization of business cycle fluctuations in which the role of financial conditions and nonlinear dynamics are explicitly incorporated. We emphasize that the sources of instability in an economy cannot be associated exclusively with the real or financial sectors, and we incorporate the idea that financial conditions are both important sources of instability and possible nonlinear propagators of other sources of instability. We test the propagation mechanisms of such conceptualization using a Bayesian Threshold Vector Autoregression model for the US economy.

A significant portion of the work published on firm investment adapts models that operate on an “average firm” assumption, which is different from the investment behavior of a modal firm. This study employs a Bayesian quantile regression model to explore the investment rates in the United States and finds, first, that the firms with higher investment rates have a higher responsiveness to the valuation ratio and lower responsiveness to the profit rate, and, second, that there is a decline in the responsiveness of firm investment to these factors in recent years. The paper also emphasizes the role of autonomous investments in determining firm-level investment rates, based on differing sectoral factors.

We model the dimensions of decision making that give rise to statistical regularities in Tobin's q. Both the stock market speculators and the firm manager observe the Tobin’s q and take actions, yet it is only the manager that can control the firm’s capital stock and it is mostly the stock market speculators that determine the value of a firm’s stock. We incorporate the manager's and speculator's decision process explicitly to analyze the accumulation process for publicly-traded US firms.